Science

For four decades, climate models have exhibited a wide range of equilibrium climate sensitivities, the equilibrium surface temperature increase resulting from doubling of atmospheric CO2concentrations.The uncertainty in climate sensitivity estimated from different generations of climate models is dominated by uncertainties about how tropical low clouds respond to global warming. The main goal of this study is to examine whether the response of the low-clouds to warming is linked to an important characteristics of climatological low clouds, the vertical distribution of the clouds.

Approach

 The First, the vertical distribution of climatological tropical low clouds is characterized by a shallowness index in 21 climate models. Then the shallowness index is connected to changes in the shortwave cloud radiative forcing per degree warming in abrupt4xCO2 simulations. Finally, the role of boundary layer turbulence and shallow convection in shaping the vertical distribution of tropical low clouds is examined.

Impact

Our analysis have shown that in current climate model, greater shallowness of low clouds in weak-subsidence regimes is associated with greater climate sensitivity. How shallow low clouds are in a given model is controlled by the competition between parameterized convection drying and turbulent moistening, which together account for the total parameterized moisture mixing in a model. As the climate warms, low clouds in a model may become shallower or deeper, depending on the change of total moiture mixing by parameterized convection and turbulence. This study suggests that model developmetns that improve how low clouds are distributred vertically may increase the reliability of how the low-cloud response to climate chagne is simulated. Reliable verification of the vertical structure of low clouds in models will also require a continuous effport to monintor three-dimensional cloud structures observationally.

Acknowledgments

This work was supported by the Department of Energy's Regional and Glboal Climate Model Program under the project "Identifying Robust Cloud Feedbacks in Observations and Model". We thank Bjorn Stevens, Louise Nuijens, Steve Klein and Peter Caldwell for useful discussions on this topic. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output.